Clinical Utility and Diagnostic Validity of the Hierarchical Taxonomy of Psychopathology for Borderline Personality Disorder

Background: The hierarchical taxonomy of psychopathology (HiTOP) aims to address the limitations of traditional nosologies. This model organizes borderline personality disorder (BPD) along two dimensions: The distress sub-factor of negative affectivity and antagonism. Objectives: For the HiTOP model to be effectively integrated into clinical practice, its clinical utility must be established. This study aimed to assess the clinical utility and diagnostic validity of HiTOP in diagnosing BPD. Methods: This cross-sectional study included 113 inpatients with a primary diagnosis of BPD and 100 nonclinical individuals. The Structured Clinical Interview for diagnostic and statistical manual of mental disorders (DSM-5) Personality Disorders, Structured Clinical Interview for DSM-5-Screening Personality Questionnaire, Personality Inventory for DSM-5, and the Personality Assessment Inventory–Borderline Features Scale were used for BPD diagnosis and severity assessment. Multiple regression analyses were conducted on BPD-HiTOP-related and other maladaptive personality domains to identify the best predictive factors for BPD. Borderline personality disorder scales were created based on the regression algorithms. Receiver operating characteristic (ROC) analyses and diagnostic efficiency statistics were used to assess the relative diagnostic efficiency of these scales. Results: Regression analyses indicated that negative affectivity and disinhibition significantly predicted BPD severity, whereas antagonism did not. The ROC analysis demonstrated that both the HiTOP-BPD algorithm (antagonism/negative affectivity) and the proposed BPD algorithm (disinhibition/negative affectivity) showed excellent accuracy. Regarding diagnostic validity, the proposed BPD algorithm exhibited higher sensitivity and specificity levels compared to the HiTOP-BPD algorithm. Conclusions: These findings support the clinical utility of the disinhibition-negative affectivity algorithm in diagnosing BPD.